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Adaptive process optimization using functional-link networks and evolutionary optimization
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DOI：10.1016/0967-0661(96)00173-6.png)
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Abstract
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This paper reports on a process optimization software system which improves plant operating performance on-line and continuously. The system combines neural network modeling and multi-objective constrained nonlinear optimization capabilities, Application of the system to process modeling and optimization in general, and in the specific domain of coal fired furnaces, is addressed, and results of applying the system are reported.
Keywords:
neural networks
functional-link network
evolutionary programming
combustion
process optimization
supervisory control, optimal control
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